With their ever-increasing performance and lowering cost, many robots (e.g., machines configured to automatically/autonomously execute physical actions) are now extensively used in many fields. Robots, for example, can be used to execute various tasks (e.g., manipulate or transfer an object through space) in manufacturing and/or assembly, packing and/or packaging, transport and/or shipping, etc. In executing the tasks, the robots can replicate human actions, thereby replacing or reducing the human involvement that would otherwise be required to perform dangerous or repetitive tasks.
However, despite the technological advancements, robots often lack the sophistication necessary to duplicate human sensitivity and/or adaptability required for executing more complex tasks. For example, manipulation robots often lack the granularity of control and flexibility in the executed actions to account for deviations or uncertainties that may result from various real-world factors. Accordingly, there remains a need for improved techniques and systems for controlling and managing various aspects of the robots to complete the tasks despite the various real-world factors.